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Wide-bandgap semiconductors have demonstrated considerable potential for fabricating solar-blind ultraviolet (SBUV) photodetectors, which are extensively used in both civilian and military applications. Despite this promise, the limited variety of semiconductors with suitable bandgaps hampers the advancement of high-performance SBUV detectors. In this study, we synthesized CdPS3 transparent single crystals using the chemical vapor transport (CVT) method. Density functional theory (DFT) calculations suggest that the bandgap of CdPS3 decreases as the material's thickness increases, a finding corroborated by subsequent absorption spectra and photoelectric response measurements. The as-prepared CdPS3 nanosheets were employed as channels in photodetectors, demonstrating outstanding photoelectric performance in the solar-blind ultraviolet range (at 254 and 275 nm) with high responsivity (0.3 A/W), high specific detectivity (5.5 × 109 Jones), rapid response speed (2.6 ms/3.4 ms), and exceptionally low dark current (2 pA). It is noteworthy that these nanosheets exhibit almost no sensitivity to 365 nm and visible light irradiation, attributable to the direct carrier transition beyond the broad bandgap in CdPS3. Furthermore, high-quality imaging was achieved under different gate voltages using 275 nm ultraviolet light, underscoring the potential of CdPS3 as a new material for high-performance SBUV optoelectronic detection. [ABSTRACT FROM AUTHOR]

Temporal compressive CDI utilizes single-exposure snapshot compression sampling in the frequency domain to visualize the dynamic process of CDI. Due to the lack of effective frequency domain prior information constraint, the traditional temporal compressive CDI method has limited imaging quality. In order to achieve high-quality dynamic reconstruction at high frame rates, a score-based diffusion model in frequency domain is used to extract the prior gradient distribution of the target in the complex frequency domain. Subsequently, this information is harmoniously woven into the physics-driven iterative phase recovery reconstruction process to restore multi-frame high-quality images. Simulation and experimental outcomes have demonstrated that the proposed technique surpasses conventional methods, delivering enhanced structural details and a reduction in artifact. The highest achieved PSNR and SSIM values are 37.25 dB and 0.997, respectively. The proposed method has equally well performance on targets across datasets, demonstrating the strong generalization of the method. [ABSTRACT FROM AUTHOR]

The frequency diversity array (FDA) is subject to its own property, which will cause the problem of target blurring in imaging. The existing FDA deblurring target imaging method generally adopts the design of nonlinear frequency increments, but it also brings new problems associated with sidelobe increases. Aiming at the problem of frequency diversity array image deblurring, this letter proposes an FDA deblurring target imaging method. Starting from the mechanism through which the blur is caused by the mutual influence of frequency increments, a mathematical model of image domain blur is established. A deconvolution method is proposed to achieve high-quality imaging without blur under arbitrary frequency increments of FDA. What's more, a low-error imaging method based on ripple transfer is proposed to deal with the problem of error accumulation in deblurring. Finally, the effectiveness of the algorithm is verified by experimental simulation. [ABSTRACT FROM AUTHOR]

Total-body (TB) PET/CT is a groundbreaking tool that has brought about a revolution in both clinical application and scientific research. The transformative impact of TB PET/CT in the realms of clinical practice and scientific exploration has been steadily unfolding since its introduction in 2018, with implications for its implementation within the health care landscape of China. TB PET/CT's exceptional sensitivity enables the acquisition of high-quality images in significantly reduced time frames. Clinical applications have underscored its effectiveness across various scenarios, emphasizing the capacity to personalize dosage, scan duration, and image quality to optimize patient outcomes. TB PET/CT's ability to perform dynamic scans with high temporal and spatial resolution and to perform parametric imaging facilitates the exploration of radiotracer biodistribution and kinetic parameters throughout the body. The comprehensive TB coverage offers opportunities to study interconnections among organs, enhancing our understanding of human physiology and pathology. These insights have the potential to benefit applications requiring holistic TB assessments. The standard topics outlined in The Journal of Nuclear Medicine were used to categorized the reviewed articles into 3 sections: current clinical applications, scan protocol design, and advanced topics. This article delves into the bottleneck that impedes the full use of TB PET in China, accompanied by suggested solutions., (© 2024 by the Society of Nuclear Medicine and Molecular Imaging.)

Small multi-rotor unmanned aerial vehicles (SMR-UAVs) are a promising platform for low-cost synthetic aperture radar (SAR) systems. However, SMR-UAVs usually suffer from serious position errors due to their unstable motion and low actuary position sensors, and autofocus is an indispensable step for their high-quality imaging. An efficient back-projection autofocus method is proposed for SMR-UAV SAR systems by the principle of minimum entropy. The position error estimation model via minimum entropy is derived. The conjugate-gradient method is used to efficiently estimate the position errors. Moreover, to improve the computing efficiency, the strong scatterer areas are estimated as the input of entropy estimation. The effectiveness of the algorithm is demonstrated using both simulation and experimental data.

Small multi-rotor unmanned aerial vehicles (SMR-UAVs) are a promising platform for low-cost synthetic aperture radar (SAR) systems. However, SMR-UAVs usually suffer from serious position errors due to their unstable motion and low actuary position sensors, and autofocus is an indispensable step for their high-quality imaging. An efficient back-projection autofocus method is proposed for SMR-UAV SAR systems by the principle of minimum entropy. The position error estimation model via minimum entropy is derived. The conjugate-gradient method is used to efficiently estimate the position errors. Moreover, to improve the computing efficiency, the strong scatterer areas are estimated as the input of entropy estimation. The effectiveness of the algorithm is demonstrated using both simulation and experimental data. [ABSTRACT FROM AUTHOR]

Localisation of an active capsule endoscope inside the stomach has different challenges. One of them is the estimation of the capsule's roll angle. Another challenge is adjusting the distance between the capsule and the stomach to achieve high‐quality imaging in the region of interest. In this study, an optimised image‐guided localisation (O‐Localisation) method is proposed to estimate the roll angle and the scale factor between the consecutive frames. The distance between the capsule and walls of the stomach can be adjusted using the suggested fuzzy adjuster, which is developed based on the estimated scale factors and calibration parameters. This new method is only based on visual information extracted from wireless capsule endoscope video frames. The results show that this method can accurately estimate the rotation angles and scale factors with errors <0.2% for the angles up to 90° and 0.3% for the scales up to 5, respectively. The method is robust to the brightness changes up to 80% with a maximum error of 0.3%. The computational time is about 1 s and can be considered near real‐time for this application. Accordingly, the O‐Localisation method as a real‐time, robust and precise method for capsule localisation can provide a more efficient controllable and steerable capsule endoscopes. [ABSTRACT FROM AUTHOR]

Electrical impedance tomography (EIT) is a new medical imaging technology that is used to estimate changes in the internal conductivity based on measurements of the border voltage disturbance. However, the generalized inverse operator of image reconstruction for EIT is ill-posed and ill-conditioned. In order to improve reconstruction quality, the structured sparse representation is integrated into the iterative process of the Symkaczmarz algorithm for EIT image reconstruction in this paper. The sparsity prior and the underlying structure characteristics of conductivity reconstruction are considered in the proposed algorithm. Both simulation and experiment results indicate that the proposed method has feasibility for pulmonary ventilation imaging and great potential for improving the image quality. [ABSTRACT FROM AUTHOR]

Image quality has long been deemed a key challenge for electrical impedance tomography (EIT). High-quality image is of great significance for improving the qualitative and quantitative imaging performance in biomedical or industrial applications. In this paper, a novel image reconstruction algorithm for EIT using adaptive group sparsity constraint is proposed to obtain enhanced image quality. The proposed algorithm takes both the underlying structure characteristics and sparsity prior of the conductivity distribution into account to promote a solution with group sparsity structure and reduce the degree of freedom. Specifically, an adaptive grouping method is incorporated for efficient and dynamic pixel grouping when the conductivity distribution does not have a fixed structure or the prior knowledge of the structure is unavailable. Numerical simulation and phantom experiments are performed to validate the proposed algorithm. The results are compared with those using the Landweber iteration, total variation regularization, and l1 regularization. Both simulation and experiment results confirm the significantly improved tomographic imaging quality using the proposed algorithm, which demonstrates great potential for multiphase flow imaging and biological tissue imaging. [ABSTRACT FROM AUTHOR]

This letter proposes an imaging receiver scheme for an indoor multiple-input-multiple-output (MIMO) visible light communication (VLC), in which a fisheye lens with ultrawide field-of-view is used for high-quality imaging, so it can realize omnidirectional receiving and provide high-spatial diversity for decoding of the MIMO signals. In addition, the fisheye lens projects planar and small-sized images, which means that the integration with compact planar receiver array is feasible. Using the polynomial projection model, the optical intensity on the receiving plane is obtained, which is in accordance with the experimental result and shows that the images of the light-emitting diodes are clearly separated. The simulation results indicate that low correlations of the channel matrix are achieved, so high spectral efficiency is realized with various receiver positions under indoor circumstance. Consequently, this fisheye-lens-based imaging receiver is a potential candidate for high-performance indoor MIMO VLC applications. [ABSTRACT FROM PUBLISHER]

For quality verification, an X-ray inspection process is commonly being used for evaluating obscured and defective solder joints in surface-mount technologies, such as ball grid arrays and flip chips. Integrated circuits subjected to any form of radiation, i.e., ionizing or nonionizing, may incur some amount of damage depending on the absorbed dose. Though most X-ray inspections for high-quality imaging require ionizing dose amounts that are considered inconsequential for device failure or non-functionality, the degree of latent damage must be carefully considered. This paper discusses X-ray-induced vulnerabilities of high-density dynamic random access memory exposed to low ionizing radiation levels typical in X-ray inspection systems. We look at critical parameters and their sensitivity in relation to varying dose amounts of X-ray irradiation. In consideration of different methodologies of reducing radiation dose amounts and limiting device exposure, we propose a procedure for attenuating potentially harmful X-ray radiation levels while preserving quality images. [ABSTRACT FROM PUBLISHER]